The present invention relates to machine vision safety systems, and more particularly to a method and apparatus for automatically determining setup parameters in machine vision safety systems.
Industrial safety requires protection of operators, maintenance personnel, and bystanders from potential injuries from hazardous machinery or materials. In many cases the hazards can be reduced by automatically sounding an alarm or shutting off a process when dangerous circumstances are sensed, such as by detection of a person or object approaching a dangerous area. Industrial hazards include mechanical (e.g., crush, shear, impalement, entanglement), toxic (chemical, biological, radiation), heat and flame, cold, electrical, optical (laser, welding flash), etc. Varying combinations of hazards encountered in industrial processing can require numerous simultaneous safeguards, increasing capital expenses related to the process, and reducing reliability and flexibility thereof.
Machine tools can be designed with inherent safety features. Alternatively, hazards of machines or materials may be reduced by securing an enclosed machine or portions of the adjacent processing area during hazardous production cycles. Mechanical switches, photo-optical light-curtains and other proximity or motion sensors are well known safety and security components. These types of protection have the general disadvantage of being very limited in their ability to detect more than a simple presence or absence (or motion) of an object or person. In addition, simple sensors are typically custom specified or designed for the particular machine, material, or area to be secured against a single type of hazard. Mechanical sensors, in particular, have the disadvantage of being activated by unidirectional touching, and they must often be specifically designed for that unique purpose. They cannot sense any other types of intrusion, nor sense objects approaching nearby, or objects arriving from an unpredicted direction. Even complicated combinations of motion and touch sensors can offer only limited and inflexible safety or security for circumstances in which one type of object or action in the area should be allowed, and another type should result in an alarm condition. Furthermore, such increased complexity reduces reliability and increases maintenance costsxe2x80x94a self-defeating condition where malfunctions can halt production.
It is known to configure a light curtain (or xe2x80x9clight barrierxe2x80x9d) by aligning a series of photo-transmitters and receivers in parallel to create a xe2x80x9ccurtainxe2x80x9d of parallel light beams for safety/security monitoring. Any opaque object that blocks one of the beams will trigger the photo-conductive sensor, and thus sound an alarm or deploy other safety measures. However, since light beams travel in straight lines, the optical transmitter and receiver must be carefully aligned, and are typically found arranged with parallel beams. These constraints dictate that light curtains are usually limited to the monitoring of planar protection areas. Although mirrors may be used to xe2x80x9cbendxe2x80x9d the beams around objects, this further complicates the design and calibration problems, and also reduces the safe operating range.
One major disadvantage of a light-curtain sensor is that there is a minimum resolution of objects that can even be detected, as determined by the inter-beam spacing. Any object smaller than the beam spacing could penetrate the xe2x80x9ccurtainxe2x80x9d (between adjacent beams) without being detected. Another disadvantage is that the light curtain, like most point-sensors, can only detect a binary condition (go/no-go) when an object actually interrupts one or more beams. Objects approaching dangerously close to the curtain remain undetected, and a fast-moving intruding object might not be detected until too late, thus forcing the designers to physically position the curtains farther away from the danger areas in order to provide the necessary time-interval for activating safety measures. For large machines this would deny access to large adjacent areas, or require physical barriers or other alarm sensors to provide the requisite security. In addition, the safe operating range between the photo-transmitter and corresponding receiver can be severely limited in cases where chips, dust, or vapors cause dispersion and attenuation of the optical beam, or where vibrations and other machine movements can cause beam misalignment.
Furthermore, light curtains are susceptible to interference from ambient light, whether from an outside source, or reflected by a nearby object. This factor further limits the applications, making use difficult in locations such as outdoors, near welding operations, or near reflective materials. In such locations, the optical receivers may not properly sense a change in a light beam. Still further, light curtains are often constructed with large numbers of discrete, sensitive, optical components that must be constantly monitored for proper operation to provide the requisite level of safety without false alarms. It is axiomatic that system reliability is reduced in proportion to the number of essential components and the aggregation of their corresponding failure rates. Microwave curtains are also available, in which focused microwave radiation is sent across an area to be protected, and changes in the energy or phasing at the distant receiver can trigger an alarm event. Microwave sensors have many of the same disadvantages of light curtains, including many false alarm conditions.
Ultrasonic sensor technologies are available, based upon emission and reception of sound energy at frequencies beyond human hearing range. Unlike photoelectric sensing, based upon optically sensing an object, ultrasonic sensing depends upon the hardness or density of an object, i.e., its ability to reflect sound. This makes ultrasonic sensors practical in some cases that are unsuitable for photoelectric sensors, however they share many common disadvantages with the photoelectric sensors. Most significantly, like many simple sensors, the disadvantages of ultrasonic sensors include that they produce only a binary result, i.e., whether or not an object has sufficiently entered the safety zone to reach a threshold level. Similar problems exist for passive infrared sensors, which can only detect presence or absence of an object radiating heat, typically based upon pyroelectric effects, that exceeds a predetermined threshold value. Such heat sensors cannot be used effectively near machines that generate heat or require heat, or where ambient sunlight may interfere with the sensor.
Video surveillance systems having motion detection sensors are also known for automatically detecting indications of malfunctions or intruders in secured areas. These types of known sensors are limited to the simple detection of change in the video signal caused by the perceived movement of an object, perhaps at some pre-defined location (e.g., xe2x80x9cupper left of screenxe2x80x9d). Analog video surveillance systems are susceptible to false alarms caused by shadows coming into view that cannot be distinguished from objects.
In addition, it is difficult to use these systems for monitoring of a precise area, since the guarded area should be as small as possible. Also, video motion detectors for surveillance are mounted with a perspective on the viewed scene making it difficult to set precise zones. There is typically also a non-uniform detection capability across the scene. Video motion detectors can be useful for general surveillance operations, but the stringent requirements against false positives and false negatives (missing something) do not permit their use for safety devices.
Furthermore, in video motion detectors available in the prior art, a low-contrast object can enter the area without triggering an alarm. Such systems also require sufficient ambient light to uniformly illuminate the target area in order to properly view the intruding objects. Additional lighting can cause its own problems such as reflections that affect the workers, machines or other sensors, or cause shadows that impinge upon adjacent safety areas and cause false alarms. These and other disadvantages restrict the application of analog video surveillance systems, like the mechanical switch sensors, to simple applications, or where combined with other sensor types.
More recently, proximity laser scanners (PLS) have been used to detect objects within a defined area near the PLS sensor. These systems are also known as Laser Measurement Systems (LMS). The PLS technology uses a scanning laser beam and measures the time-of-flight for reflected light to determine the position of objects within the viewing field. A relatively large zone, e.g., 50 meter radius over 180 degrees, can be scanned and computationally divided into smaller zones for early warnings and safety alarm or shutdown. However, like many of the other sensor technologies, the scanning laser systems typically cannot distinguish between different sizes or characteristics of objects detected, making them unsuitable for many safety or security applications where false alarms must be minimized.
Significantly, the scanning laser systems typically incorporate moving parts, e.g., for changing the angle of a mirror used to direct the laser beam. Such moving parts experience wear, require precision alignment, are extremely fragile and are thus unreliable under challenging ambient conditions. Even with a system that uses fixed optics for refraction or diffraction fields, the components are fragile and susceptible to mis-alignment. Another disadvantage of such systems is that they generally have a flat field of view that must be arranged horizontally to protect an adjacent floor area. This leads to multiple problems, including being susceptible to physical damage or bumping, which increases false alarms and maintenance. Furthermore, the protected area is theoretically infinite, thus requiring the use of solid objects or screens to limit the protected area for applications near other moving objects.
3-D video safety implementations are known. In such implementations, stereopsis is used in determining a 3-D location of an object with respect to cameras, or a defined reference point. A 3-D difference can then be derived and compared with a model view. However, to locate objects in 3-D space requires a binocular (or trinocular) image set. It also may increase the cost and maintenance of equipment. In addition, 3-D calculations for matching and determining alarms conditions may be time consuming. For an application where the camera is mounted overhead to view a target, the area within view is conical and the first part of a person coming into view would be very close to the floor (i.e., the feet), making it more difficult and error-prone to quickly detect as a height difference above the floor. To obtain the necessary coverage, the cone needs to be larger, the camera needs to be higher from the floor, and the image resolution is thus disadvantageously diminished. With the larger cone of vision, the potential false alarm rate is also increased. These disadvantages may accumulate to such an extent that the system is not reliable enough for use in applications for protecting severe hazards where false alarms or false positives cannot be tolerated.
Users of even the most sophisticated video safety curtains such as those taught in the co-pending application Ser. No. 09/562,261 must typically define dangerous spaces or monitored spaces within an image and communicate the spatial parameters to an image processor. Portions of the image outside of dangerous areas or monitored spaces may be ignored by the image processor thereby increasing processing efficiency.
The administrator of a video safety curtain system often desires to specify a safety zone or perimeter within the control image at setup time. In certain systems, the administrator interacts with the system to superimpose boundary lines over a control image on a computer monitor using graphical input tools thereby defining safety zone perimeters or limits. The image processor recognizes these manually input setup lines as boundaries of a safety zone and can be configured to ignore features that are located outside of the configured boundary area. As recited in the co-pending application Ser. No. 09/562,261, machine vision safety curtain applications use at least two separate processing methods to determine whether an object has crossed a boundary into a safety zone. One known method determines whether an object has crossed into a safety zone by comparing each new image frame to a control image of a training scene such as a tape boundary and determining whether particular background features of the control image, such as the tape boundary, are found. If the control background features can not be found in an image frame then the processor determines that an object is occluding the background features and an alert condition is implemented. Another method implements a pixel by pixel comparison of each image frame to a control image and implements an alarm condition if any significant differences are found.
Systems which use the background occlusion method require a perimeter to be marked by adhesive tape, painted lines, patterns or similar recognizable features, so that the perimeter can be recognized by the image processor. The tape or painted lines provide control image background features that are scanned for occlusions. The system administrator uses graphical interface tools to observe the image of the tape or marking features and manually define the corresponding safety zone.
Systems which use the difference method also typically require an administrator to manually define the safety zone on the control image using graphical interface tools. While such systems are not required to recognize a perimeter by means such as tape or painted lines, a perimeter is still manually defined to eliminate unnecessary processing and to define a protected area.
At least one current method of setting up a video safety curtain is completely manual. The following procedure is used:
compute the buffer distance based on a fundamental constraint equation; ensure that no points are too close to the center of the camera based on a distance constraint equation; ensure that the camera is contained within the perimeter; lay marking tape along the outer perimeter; capture an image of the area being viewed; and use a graphical tool to manually layout the outer perimeter (protection zone) using the marking tape as a visual cue.
This last step can be extremely tedious, especially if it is done frequently. Known Video Safety Curtains typically use lenses with a wide angular field of view to cover a large area from a given height. One disadvantage of using a wide field view is that the pixel size is increased. Therefore, the software has a minimum detectable feature size in pixels and the size of the smallest detectable object increases. Another disadvantage is an increased optical distortion across the field-of-view. In an uncalibrated system it is only possible to approximately ensure that the minimum detectable feature size is not too large.
Manual input methods of defining a safety areas on a control image disadvantageously allow opportunities for error. System administrators may improperly set-up a video safety screen by mislocating perimeter lines with the graphical input tools. Such mislocated perimeter lines may present dangerous conditions whereby no alert condition would be implemented when a person or object moves into a dangerous space.
Manual setup procedures cause inefficiencies where certain safety areas may be difficult to define or certain graphical input tools may be difficult to use. The requirement for additional equipment for the operator to use a graphical user interface degrades system reliability, increases operator training time, and increases system capital and operating expense. These inefficiencies are compounded where an administrator is required to set up multiple systems. Furthermore, manual setup may not be consistent when performed by different system administrators. Such inconsistent setup conditions prevent a system from achieving optimum performance because, for example, excessively large or small setup parameters may be specified which prevent a system from performing at an optimal level.
Often a camera will vibrate out of its original alignment or may be accidentally jarred out of alignment. An administrator is then required to repeat a manual setup procedure, further reducing system efficiency.
Certain applications require a safety zone perimeter to be located a specific distance from a machine or dangerous area. A safety curtain around a piece of automatic assembly equipment in a factory, for example, may be expected to protect persons from moving closer than a specified distance to the equipment. However, a monocular system has no automatic method for converting images into distances. Manual setup procedures disadvantageously do not provide a means for defining a perimeter at a measured distance from a machine or dangerous area.
Distances between points of an image in a machine vision system can be roughly measured in pixels. Camera lens distortion, processor sampling error and system non-linear distortion combine to undesirably prevent straight forward conversion of distance values from image units to physical units such as centimeters. Most 2-D video safety systems do not directly measure real world distances between objects without pixel-to-object size calibration.
3-D protection zones of a video safety screen can be defined as volumes whose perimeters depend upon placement of cameras relative to the protection zone as well as upon specified or marked protection zone borders. Particular protection zone spaces may be generally pyramid shaped, for example, where cameras are mounted above a danger zone viewing downward onto a rectangular marked border area. Another protection zone may be generally cone shaped, for example, where cameras are mounted above a danger zone viewing downward onto a circular marked border area. Irregularly marked border areas and offset camera positions can combine to form any number of 3-D protection zone spaces.
Certain video safety curtain systems, including occlusion type video safety curtains, monitor only the outside curtain of a 3-D protection zone space. The curtain corresponds to a thin volume contiguous to the surface of the 3-D protection zone and has a thickness which corresponds to the border marking tape width at the base of the protection zone and which thickness decreases toward the camera position.
Because of this limitation, a danger exists wherein an object or person may be within the protection zone and completely inside the curtain at system startup time or may move inside the curtain between system scan times or faster than may be reliably detected during processing of a detection cycle. Such an object would not be detected by the safety curtain system, thus creating an undesirable hazardous condition. System operators can not easily determine where these danger zones exist within the protection perimeter.
The present invention provides a two-dimensional (2-D) machine-vision safety-solution involving a method and apparatus for performing high-integrity, high efficiency machine vision. A 2-D video data image of the background in an empty safety zone is captured over time. Each data element of sequentially captured images is compared with corresponding elements of a digitally filtered image of a number of previous captures, in order to determine the cumulative magnitude of contiguous changes. The resulting image is segmented to group areas that are contiguous features. These areas are further processed to discriminate shadows from objects by comparing the changed features of the observed surface against the previously observed features of the vacant background in the safety zone. Further processing results in rapid identification of alarm conditions in accordance with prescribed criteria. To further eliminate shadows, a monochromatic source of illumination can be located near the camera to illuminate the protected area centrally, and by applying a band-pass filter on the sensing device.
An object, multiple objects, or an area being monitored are collectively called the xe2x80x9ctargetxe2x80x9d for purpose of discussion. The target is being protected from encroachment by another foreign object, called the xe2x80x9cintruder.xe2x80x9d
According to the invention, the 2-D machine-vision safety-solution apparatus includes an image acquisition device such as one or more video cameras, or digital cameras, arranged to view light reflected from a target scene, such as a safety zone near a dangerous machine. The cameras pass the resulting video output signal to a computer for further processing. The video output signal is connected to the input of a video processor adapted to accept the video signal, such as a xe2x80x9cframe grabberxe2x80x9d sub-system. Time-sequenced video images from the camera are then synchronously sampled, captured, and stored in a memory associated with a general-purpose computer processor. The digitized image in the form of pixel information can then be stored, manipulated and otherwise processed in accordance with capabilities of the vision system. The digitized images are accessed from the memory and processed according to the invention, under control of a computer program. The results of the processing are then stored in the memory, or may be used immediately to activate other processes and apparatus adapted for the purpose of taking further action, depending upon the particular industrial application of the invention.
In further accord with the invention, the machine-vision safety solution method and apparatus involves storing not only a fixed number of previous captured images in a memory buffer, but also storing a previous filtered output image. A filtered image is created by taking the buffered samples of the video scene and running them through a pixel-oriented low-pass filter. A low-pass filter is designed to prevent high-frequency noise, such as vibrations and flickering light, from creating changes in the filtered image. Each pixel is digitally filtered against the corresponding pixel over a predetermined number of prior images. The filtered image is then compared with each new image to be tested to determine if there have been any sudden changes in the image of the viewed area, the combination thus operating as a high-pass filter. Changes detected by the high-pass filter are then processed to determine if there is a large cumulative magnitude of contiguous changes. A change large enough to exceed a threshold level results in an alarm condition being reported.
Determining the size of the cumulative magnitude of contiguous changes is carried out by using a segmentation step. Segmentation refers to the process of identifying pixels forming a contiguous line segment (xe2x80x9cedgexe2x80x9d) or contiguous area (xe2x80x9cblobxe2x80x9d), and characterizing such segments according to their location, size and orientation. Further processing of the resulting segments is much faster than processing individual pixel data. Segmentation may be performed using a xe2x80x9cwatershedxe2x80x9d process which quickly determines the location and size of a change by xe2x80x9cfilling inxe2x80x9d valleys that appear between change gradients of the received gray-scale values in the change image.
When using ambient light as the light source on the protected area, shadows of objects outside of the protected area may fall within the viewed perimeter. These shadows can be misinterpreted as intruders and cause false alarms. In one alternative embodiment, a strong but diffused light source located near the camera is used. This arrangement tends to avoid confusion of shadows for an object, since only shadows of objects within the observed area would be visible, provided the system light source is sufficiently strong with respect to ambient light sources reaching the target area. This also reduces the chances that an object might penetrate a poorly lit portion of the target area without triggering a visible change.
In another alternative embodiment, the light source located near the camera produces a diffused light in the near-infrared (IR) spectrum, and the camera lens is filtered to attenuate light at other wavelengths. Image capture, filtering, and blob segmentation and detection are then carried out as above. This arrangement improves the rejection of ambient shadows, especially where ambient light is fluorescent rather than incandescent or natural light having substantial unfiltered components near IR. This embodiment is also relatively simple and processing is relatively fast. The self-contained lighting arrangement also increases the ability to detect intruders where ambient light does not provide adequate uniform light for object detection.
In another alternative embodiment, a textured background is used as a static target and viewed under ambient light to create an artificial contrast with respect to intruding objects. Images are captured and filtered for high-pass and low-pass outputs. In addition, a gradient image is computed directly from the present digitized image source. The segmentation step is then performed on the output of the high-pass filter to create a mask image. Edge-detection is then implemented by masking the output of the low-pass filter, and calculating edges in the low-pass filtered image. These edges are then compared to the gradient image. The result is then processed to detect sudden changes in the texture being viewed. When an intruding object comes between the textured background and the camera the detected texture of the intruder is highly likely to be different from that of the background. This implementation provides superior rejection of changes caused by ambient shadows falling on the target. It also reduces the chances that the system will fail to notice an object having low contrast with respect to the background, since the texture creates an artificial contrast against which most intruder objects will be plainly distinguishable.
In another alternative embodiment, in addition to the textured background described above, the system includes a light source located near the camera producing a diffused light in the near-infrared (IR) spectrum, and the camera lens is filtered to attenuate light at other wavelengths. Since near-IR light behaves like visible light, the same texture decorations can be used as above for use with ambient light or overhead light. Alternatively, texture can be implemented using inks or paints that fluoresce under near-IR but remain invisible in ambient light. In addition to the advantages described above, this implementation reduces the problems caused by insufficient ambient light.
In another alternative embodiment, the light source located near the camera produces a modulated light in the near-infrared (IR) spectrum, and the camera lens is filtered to attenuate light at other wavelengths. Two channels of source images are collected nearly simultaneously and filtered: one with the IR light on, and one with ambient light only. Each channel results in a difference image and the difference between the two difference images is calculated and processed for segmentation. Interference such as shadows will occur in both channels and be cancelled out. The result is then used to determine whether a viewed change is due to an object or a shadow of a non-intruding object, since only an object within the perimeter would cause a change under the IR source. Another way to implement the two image channels is to use two separate cameras: one filtered to reject all but near-IR light and one for receiving images under ambient light. Although it requires additional equipment, this implementation would eliminate the ambient shadow problem while also reducing noise that could cause false alarms.
The advantages of using a Video Safety curtain over Light Curtains and Time-of-Flight Lasers are numerous. Even further advantages are achieved by adding an Autosetup capability, which is possible only in video based systems. The present invention further provides a method and apparatus for implementing an automatic setup of a video safety curtain.
At least one digital video camera is mounted so that it has a view of the danger zone and a surrounding protection zone. The danger zone is defined as an area where intrusion by persons or objects is undesirable or harmful. The protection zone is defined as an area surrounding the danger zone in which the presence of an intruding object or person is intended to cause an alert condition thereby, stopping the machine, deterring the person or preventing the object from reaching the danger zone.
An image processor scans the control image and locates the distinctive border, such as striped adhesive tape using a segmenting/filtering/pattern finding algorithm. The image processor considers the location of the tape as a boundary of the protection zone without requiring any manual input. A post-processing step is performed to generate the perimeter/safety zone border lines in a format that can be used by a video safety curtain. The border lines are then communicated to the safety curtain processing system and used in place of manual set-up lines.
While digital cameras typically provide two dimensional information such as two dimensional array of pixel data describing a scene, certain protection zones are three dimensional spaces surrounding a danger zone. The present invention may be implemented to automatically identify or define a border of a two dimensional protection zone or a three dimensional protection zone to a video safety curtain processing system. Borders of a three dimensional protection zone may be interpolated by the processing system according to placement of border line markings, placement of a camera relative to the protection zone and the nature of the threat.
Distances in pixels between image points may be transformed into actual distance values between objects in 3-D space. A number of image coordinates in pixels having known world 3-D coordinates in linear units are processed to develop a non-linear transform between image coordinates and 3-D world coordinates of objects. The non-linear transform may then be applied to any set of image points to determine 3-D coordinates of points on detected objects. The 3-D world coordinates may then be used to determine an object""s actual size or distance from a danger zone.
A video safety system may compute physical distances between objects at set-up time in order to set protection zone borders at a specific distance from a danger zone or offset a protection border from a marked border line by a specific distance.
A video safety system may also use a transform operation to measure sizes of objects and distances between objects independently from an auto-setup procedure. For example, a system may determine an object size or shape at run-time to disregard irrelevant objects so that only intrusion by objects having a certain size or shape may trigger an alarm condition.
The present invention defines a relationship between a maximum system scan time, an expected minimum intruder size and an expected maximum intruder approach velocity so that a system can be configured to detect an intruder while at least part of the intruder is breaching the protection zone curtain.
A significant advantage of the 2-D video motion detector implemented according to the invention is its geometry. By looking top-down on a scene where intruders may enter, the background in the scene can be controlled since the camera is looking at the floor. This gives more control over the contrast problem. Advantageously, a single camera-lighting fixture could be used such that the whole area is uniformly lit and viewed. Therefore, the detection capability (sensitivity) is uniform across the target area. This makes the arrangement less susceptible to problems caused by shadows. Implementation according to the present invention allows the setting of precise target regions that need to be protected. This is done either using visible markers on the floor during a setup procedure or by a graphic user interface overlaid on the image. Additionally, the entire area can be viewed. If the camera were mounted to one side or on the hazardous machinery itself, it would not be possible to obtain 180-degree coverage due to the viewable cone of the camera lens.
Intruding objects can be determined according to the invention without using sensors that must be specially designed, placed, or calibrated for each different type of object to be protected. The system does not rely upon any moving mechanical parts subject to the rigors of wear and tear. It is not necessary for the implementation, according to the invention to be placed very close to, or in contact with the hazard, as would be necessary for mechanical sensors. Machine vision systems offer a superior approach to security and safety sensors by processing images of a scene to detect and quantify the objects being viewed. Machine vision systems can provide, among other things, an automated capability for performing diverse inspection, location, measurement, alignment and scanning tasks.
Another feature of at least some embodiments of the invention is the ability to discriminate shadows from objects, to avoid false alarms. Similarly, when using its own light source, the system provides greater shadow immunity. In addition, the use of a near-IR light source offers the feature of additional illumination without the drawbacks of visible light, such as reflections. Similarly, near-IR is completely invisible and can be operated in what would otherwise appear to humans to be total darkness. When using a textured background, the system overcomes disadvantages caused by low-contrast intruders. Another feature of the invention is the ability to automatically store (and archive) digitized images of the scene in which an infraction of the safety or security rules existed, for later review.
Features of the present invention include an automatic setup method for a video safety curtain system which does not require manual input of safety zone perimeters. The automatic setup method advantageously increases accuracy and consistency of safety zone perimeter definitions.
Another feature of the present invention includes a video safety curtain system which is easily set up. An automatic setup procedure may be implemented by simply clicking a single button, thereby saving time and effort compared to manual setup procedures. If a camera vibrates out of alignment or is jarred out of alignment the automatic setup routine may be quickly and easily repeated to correct any offset errors. Operator workload and errors are reduced, system components are simplified and reliability is increased. The present invention also provides a video safety system having fewer moving parts such as keyboards, mice or other peripheral devices thereby providing a robust system that is particularly suitable for industrial environments.
The present invention also features an easy setup procedure which may be achieved by clicking a single button. Such an easy setup procedure is especially useful if the camera gets bumped or one changes the lens controls slightly or even if one changes a layout on the floor. The invention eliminates any need to manually tweak the setup graphically (as one would do it currently).
The present invention features enhanced accuracy, especially as compared to a manual setup which is usually prone to error. Furthermore, calibration enables accurate computation of pixel sizes across the FOV and hence an accurate minimum feature size may be determined.
The present invention also enhances safety because the various distances can be now computed automatically and a system can be checked to see if the various constraints are satisfied. This helps ensure correct operation for the Video Safety Curtain. The visualization will help in ensuring that objects that have overhangs do not infringe on the Danger zone even when they are located outside the perimeter. An optimally sized protection zone may be defined having a proper size and shape relative to a respective danger zone. Systems may thereby be optimized to process an appropriate section of each image frame without wasting processing steps or memory space.
An automatic setup procedure may be combined with a manual setup procedure. Such a hybrid approach is advantageous when the results of an automatic setup procedure are not satisfactory to an administrator. For example, an administrator may use temporarily connected manual graphical input tools to modify the automatic setup parameters.
Another feature of the present invention is a method of determining an objects physical dimensions by transforming 2-D coordinates of points on an image of an object or target into 3-D world coordinates. An object""s physical dimensions may be interpreted by a system processor to identify targets or to set-up a protection area.
Still another feature of the present invention is a method of calculating an optimum protection zone size according to a target size, target velocity, camera position and system processing speed.